Proud to Present: Our ESG Predictive Engine

2 December, 2022

Proud to Present Our ESG Predictive Engine

We are celebrating the launch of our new machine-learning ESG (Environmental, Social, and Governance) rating predictive technologies that will help support our benchmark ratings and challenge greenwashing across all large companies worldwide.

We are a small but mighty cross-disciplinary team focused on being the best at what we do, namely corporate digital responsibility (CDR) benchmark ratings. At EthicsGrade, we believe that within a few years CDR will be in mainstream ESG conversations due to increasing digitalisation. In response, we help our clients and users understand the risks of technologies. We are the only specialist provider of Environmental, Social, and Governance (ESG) data on the governance of technology across all industries. We currently operate in a niche focused on digital ethics, with the intention to move to wider ESG issues.

EthicsGrade was co-founded by Charles Radclyffe, during his time as Lead of AI at Fidelity he spotted that investors wanted an accelerating level of data on ESG, but this need was over-burdening companies with the need to report and disclose. Often there is simply no data or, perhaps worse, poor data available for investors. In 2019, Radclyffe set out to solve this problem facing many corporations when dealing with existing ESG reporting, including having to look at a multitude of issues, with much duplication and, at times, questionable relevance. This creates a reluctance to engage, poor quality data, and ultimately, we believe, greenwashing.

We know this is no simple or small challenge, as shared by Charles “developing an ESG rating is complex and complicated by the need to look behind the headlines to find evidence of real progress. Individuals react differently to ESG issues, and EthicsGrade does not judge what is a right or wrong approach. Investors, consumers, employees, and other stakeholders each see the world through their own lens and the prediction engine allows us to put multiple different lenses on the same company to provide an ESG rating specific to a stakeholder’s specific concerns.” This ability is something that makes us unique, we consider our client's points of view and share data accordingly. Our approach is unlike other market options, which have one set point of view. We have the capability to tailor our ESG rating to the specific interests of an investor, focusing on their values and priorities.

The EthicsGrade prediction engine will lighten the burden of ESG reporting for corporates by predicting the 10 key indicators of best practice digital governance to predict the overall CDR rating of a company. The best part is a company’s engagement is not required to predict an ESG rating via the EthicsGrade prediction engine ensuring investors have the information they want regardless of whether a company has the time or inclination to respond. We also create a more positive experience for companies by reducing the number of questions they need to answer on ESG to only the ones, which are the best predictors of everything else we need to know. Rather than a list of 1,000 questions on all aspects of ESG, our platform shows just the top 10. And if they have time, then the next 10, and the next 10 and so on.

So far, we have rated over 300 companies relating to their governance of technology, in sectors spanning energy, pharmaceuticals, FMCG and transport to date. Our new prediction engine will increase the number of companies that can be rated by ten times. We have generated 130 scorecards, which have been sent out to companies such as Adidas, Comcast, Deutsche Post and Starbucks; and by the end of the year, EthicsGrade will have graded the full Russell 3000 Index.

The ratings are freely available, and our data can be licensed to financial professionals including investors and proxy advisers to provide health checks, benchmarking and audit services to help develop operating models for governance and to make better investment decisions aligned with their values.